Abstract
Objectives. To identify distinct age-related trajectory classes of body mass index (BMI) z-scores from childhood to adolescence, and to examine the association of these trajectories with measures of standing sagittal spinal alignment at 14 years of age. Methods. Adolescents participating in the Western Australian Pregnancy Cohort (Raine) Study contributed data to the study (n=1 373). Age- and gender-specific z-scores for BMI were obtained from height and weight at the ages of 3, 5, 10 and 14 years. Latent class group analysis was used to identify six distinct trajectory classes of BMI z-score. At the age of 14 years, adolescents were categorised into one of four subgroups of sagittal spinal posture using k-means cluster analysis of photographic measures of lumbar lordosis, thoracic kyphosis and trunk sway. Regression modeling was used to assess the relationship between postural angles and subgroups, and different BMI trajectory classes, adjusting for gender. Results. Six trajectory classes of BMI z-score were estimated: Very Low (4%), Low (24%), Average (34%), Ascending (6%), Moderate High (26%) and Very High (6%). The proportions of postural subgroups at age 14 were; Neutral (29%), Flat (22%), Sway (27%) and Hyperlordotic (22%). BMI trajectory class was strongly associated with postural subgroup, with significantly higher proportions of adolescents in the Very High, High and Ascending BMI trajectory classes displaying a Hyperlordotic or Sway posture than a Neutral posture at age 14. Conclusions. This prospective study provides evidence that childhood obesity, and how it develops, is associated with standing sagittal postural alignment in adolescence.
Acknowledgements
Funding was received from the Australian National Health and Medical Research Council (project 323200, program 003209, fellowships 373638 and 373638), the Telethon Institute for Child Health Research, the Raine Medical Research Foundation at the University of Western Australia, Healthway, the Arthritis Foundation of Western Australia and the Arthritis Foundation of Australia. Data collection was by Rosemary Austin, Lee Clohessy, Alex D'Vauz, Monique Robinson, Nick Sloan and Diane Wood. Data processing was by Jemma Coleman and Clare Haselgrove. We would like to acknowledge the study participants and their families.
Declaration of interest: The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.